Low-complexity Joint Phase Adjustment and Receive Beamforming for Directional Modulation Networks via IRS

TL;DR

This paper proposes low-complexity joint phase adjustment and receive beamforming schemes for IRS-assisted directional modulation networks, significantly enhancing security and power efficiency in line-of-sight wireless systems.

Contribution

It introduces two novel alternating optimization algorithms for joint IRS phase shift and receive beamforming design, improving secrecy rate and computational efficiency.

Findings

Max-RPS-GAO outperforms no-IRS schemes in secrecy rate.

Max-RPS-ZF offers faster convergence and lower complexity.

Both methods significantly improve system security.

Abstract

Intelligent reflecting surface (IRS) is a revolutionary and low-cost technology for boosting the spectrum and energy efficiencies in future wireless communication network. In order to create controllable multipath transmission in the conventional line-of-sight (LOS) wireless communication environment, an IRS-aided directional modulation (DM) network is considered. In this paper, to improve the transmission security of the system and maximize the receive power sum (Max-RPS), two alternately optimizing schemes of jointly designing receive beamforming (RBF) vectors and IRS phase shift matrix (PSM) are proposed: Max-RPS using general alternating optimization (Max-RPS-GAO) algorithm and Max-RPS using zero-forcing (Max-RPS-ZF) algorithm. Simulation results show that, compared with the no-IRS-assisted scheme and the no-PSM optimization scheme, the proposed IRS-assisted Max-RPS-GAO method and Max-RPS-ZF method can significantly improve the secrecy rate (SR) performance of the DM system. Moreover, compared with the Max-RPS-GAO method, the proposed Max-RPS-ZF method has a faster convergence speed and a certain lower computational complexity.